Binarization Representation of Image Microstructure and the Application of Object Recognition
ZHANG Dongbo CHEN Zhiqiang YI Liangling XU Haixia
(The College of Information Engineering, Xiangtan University, Xiangtan 411105, China)
(Robot Visual Perception & Control Technology National Engineering Laboratory, Changsha 410012, China)
Abstract：A novel expression based on Binary Image Microstructure Pattern (BIMP) and Gray Image Micorstructure Maximum Response Pattern (GIMMRP) coding method is proposed. Through the binary coding of the 3×3 neighborhood structure of the image, the description of the microstructure of the image is obtained, and then selecting the important execution mode subset and the pooling operation to realize the representation of the whole image. In order to verify the effectiveness of the algorithm, experiments are carried out on the ORL, YALE two human face data set, MNIST, USPS two handwritten digital public data sets, as well as non-public vehicle standard data set. The results show the method has strong discriminative power and robustness and can achieve better performance than many of the latest algorithms.
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